A few months ago, IBM appeared vulnerable as the AI boom accelerated.
Investors feared that the same AI technologies driving the market rally might erode the traditional sectors that have long supported IBM.
That concern has rapidly dissipated, and a leading Wall Street tech commentator now argues that the rebound still has considerable upside.
The key question is whether the underlying drivers of that optimism can withstand scrutiny.
Wedbush lifts its IBM stock price target to $350
Wedbush increased its price target for IBM to $350, up from $320 on June 2, and reaffirmed its Outperform rating, citing incremental AI‑related gains.
The new target represents about a 15% premium to the week’s trading levels, according to Barchart, and analyst Dan Ives describes IBM’s combination of software, consulting, and infrastructure as a self‑reinforcing business flywheel.
Ives has spent the year contending that the enterprise AI buildout remains in its early stages, a point he reiterated in a recent interview with TheStreet.
The AI scare that knocked down IBM stock
In late February, IBM shares dropped 13% in a single session after Anthropic announced that its Claude model could automate the modernization of legacy COBOL code.
COBOL is a decades‑old programming language that continues to power many banking and government systems.
The underlying concern was straightforward: if AI could cheaply rewrite such code, IBM’s mainframe and consulting businesses could be jeopardized.
Wedbush countered that AI would accelerate, not eliminate, modernization efforts, and has labeled the episode the “AI Ghost Trade.”
The results provided bullish cover, with first‑quarter 2026 revenue up 9% to $15.9 billion and earnings rising 19%, as reported by IBM.
Software now anchors IBM’s strategy following years of CEO Arvind Krishna’s push toward AI.
Inside IBM’s AI engine: watsonx, Confluent, and real savings
Ives’s confidence stems from IBM’s concrete buildout rather than promotional material; the core is watsonx.data, which consolidates a company’s fragmented data for AI utilization.
IBM claims that linking AI agents to this data improves accuracy by 40% compared with conventional approaches.
The platform has been bolstered through acquisitions, notably a roughly $11 billion purchase of data‑streaming firm Confluent, as reported by Yahoo Finance.
Signals Wedbush is tracking:
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IBM’s generative AI book reached about $4 billion in annual recurring revenue, with 80% of new backlog originating from customers previously untouched by IBM, according to Benzinga.
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IBM’s Agent Catalog now provides over 200 prebuilt AI agents, as noted by Barchart, enabling clients to deploy solutions without starting from scratch.
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IBM reports $4.5 billion in internal productivity savings accumulated since 2023, with a target of an additional $1 billion this year.
Where IBM stock goes next: quantum, risks, and how it stacks up
IBM is also heavily investing in quantum computing, a field that promises to solve problems beyond the reach of classical computers.
The company plans to invest more than $10 billion over five years, according to TipRanks, and is constructing a quantum chip facility named Anderon in partnership with the U.S. Commerce Department, with each party pledging $1 billion; the announcement contributed to an 8% rise in the stock.
Ives believes IBM is still in the early stages of combining AI with quantum computing, and management targets delivering its first large‑scale fault‑tolerant quantum machine by 2029.
How IBM stacks up, and what could still go wrong
Despite the momentum, IBM has underperformed the broader market it aims to lead; the stock is up about 5% in 2026, whereas the S&P 500 has risen roughly 11% through May, per U.S. News.
The stock reached record highs in early June before slipping about 6% on June 3 amid higher oil prices and rising Treasury yields that squeezed corporate technology shares, as reported by StockStory.
What still has to go right for the bull case:
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Consulting growth must accelerate after a modest 4% rise last quarter, lagging behind software and infrastructure performance.
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The generative AI book must continue to compound as pilots transition into large, paid deployments.
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IBM must demonstrate that the COBOL fear was overstated rather than merely delayed, a risk highlighted by 24/7 Wall St. if its AI book or mainframe demand stalls.
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Quantum milestones must be met on schedule rather than slipping.
The bottom line for IBM investors
Wedbush’s $350 target reflects a bet that IBM’s AI and quantum initiatives are generating tangible revenue rather than merely generating headlines, and early results support this view.
Nevertheless, the stock trades near record highs at a premium valuation, leaving little margin for error.
Purchasing at current levels requires confidence that execution will continue to deliver quarter after quarter.